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Record W2994922700 · doi:10.1177/1010539519889765

Role of Maternal Education and Vaccination Coverage: Evidence From Pakistan Demographic and Health Survey

2019· article· en· W2994922700 on OpenAlexaff
Atta Muhammad Asif, Muhammad Akbar, Muhammad Tahir, Irshad Ahmad Arshad

Bibliographic record

VenueAsia Pacific Journal of Public Health · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsOdds ratioImmunizationPovertyLogistic regressionDemographyMedicineConfidence intervalEthnic groupVaccinationEnvironmental healthOddsImmunologyEconomic growthPolitical scienceSociology

Abstract

fetched live from OpenAlex

The aim of this study was to examine the impact of maternal education on child immunization uptake in Pakistan, both at individual and community levels. Pakistan Demographic and Health Survey data were used for analysis. Multilevel logistic regression was used to access the individual- and community-level factors associated with childhood immunization coverage. Out of 6765 children 2659 (39.3%) were fully immunized. Parents education, access to media, and wealth status have positive while ethnicity and working status of mother have a negative impact on the immunization uptake. In the community with a high percentage of educated mothers, the odds of immunized children were high (odds ratio = 1.43, 95% confidence interval = 1.14-1.80) as compared with communities with lower percentage of educated mothers. Moreover, significant variation was found in the likelihood of full immunization across communities. Both community- and individual-level factors have substantial impact on children immunization status. There is a need of improvement in maternal education, poverty alleviation, and removal of rural-urban disparities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.359
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2019
Admission routes1
Has abstractyes

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